Advances in Estimation Methods for Longitudinal Generalized Linear Latent Variable Models with Missing Data

Scientific-Disciplinary Group

13/STAT-01 - Statistics

Description

The research activity focuses on the development and evaluation of estimation methods for Generalized Linear Latent Variable Models (GLLVMs) applied to multivariate longitudinal data affected by missingness. The project combines methodological and applied components. On the methodological side, it will investigate computationally feasible and statistically accurate estimation strategies, with particular attention to limited-information approaches and their theoretical properties under different missing data mechanisms. Simulation studies will be conducted to assess their finite-sample performance. On the applied side, the proposed methods will be implemented in R, with optimized routines for efficient computation, and applied to health and socio-demographic datasets. The project will contribute both new statistical methodology and practical tools for empirical research.

Job posting website

https://bandi.unibo.it/ricerca/incarichi-di-ricerca

Funding body

ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE STATISTICHE "PAOLO FORTUNATI"

How to apply

Other

Selection process